{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制单变量分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\soft\\python\\lib\\site-packages\\seaborn\\distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "  warnings.warn(msg, FutureWarning)\n",
      "d:\\soft\\python\\lib\\site-packages\\seaborn\\distributions.py:2056: FutureWarning: The `axis` variable is no longer used and will be removed. Instead, assign variables directly to `x` or `y`.\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(0)  # 确定随机数生成器生成的数据是一样的\n",
    "\n",
    "arr = np.random.randn(100)\n",
    "\n",
    "sns.distplot(arr, bins=10, hist=True, kde=True, rug=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制双变量分布\n",
    "\n",
    "## 绘制散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({\"x\":np.random.randn(500), \"y\":np.random.randn(500)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.883151</td>\n",
       "      <td>-1.550429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.347759</td>\n",
       "      <td>0.417319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.270485</td>\n",
       "      <td>-0.944368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.969397</td>\n",
       "      <td>0.238103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.173123</td>\n",
       "      <td>-1.405963</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y\n",
       "0  1.883151 -1.550429\n",
       "1 -1.347759  0.417319\n",
       "2 -1.270485 -0.944368\n",
       "3  0.969397  0.238103\n",
       "4 -1.173123 -1.405963"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "d:\\soft\\python\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n",
      "d:\\soft\\python\\lib\\site-packages\\seaborn\\axisgrid.py:2073: UserWarning: The `size` parameter has been renamed to `height`; please update your code.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'PathCollection' object has no property 'stat_func'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-7-e9272413cc96>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjointplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"x\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"y\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"scatter\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstat_func\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"r\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m10\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mratio\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mspace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\seaborn\\_decorators.py\u001b[0m in \u001b[0;36minner_f\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     44\u001b[0m             )\n\u001b[0;32m     45\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 46\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     47\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     48\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\seaborn\\axisgrid.py\u001b[0m in \u001b[0;36mjointplot\u001b[1;34m(x, y, data, kind, color, height, ratio, space, dropna, xlim, ylim, marginal_ticks, joint_kws, marginal_kws, hue, palette, hue_order, hue_norm, **kwargs)\u001b[0m\n\u001b[0;32m   2133\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2134\u001b[0m         \u001b[0mjoint_kws\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msetdefault\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"color\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2135\u001b[1;33m         \u001b[0mgrid\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot_joint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscatterplot\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mjoint_kws\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2136\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2137\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mgrid\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhue\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\seaborn\\axisgrid.py\u001b[0m in \u001b[0;36mplot_joint\u001b[1;34m(self, func, **kwargs)\u001b[0m\n\u001b[0;32m   1732\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1733\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__module__\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstartswith\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"seaborn\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1734\u001b[1;33m             \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1735\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1736\u001b[0m             \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\seaborn\\_decorators.py\u001b[0m in \u001b[0;36minner_f\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     44\u001b[0m             )\n\u001b[0;32m     45\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m{\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 46\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     47\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     48\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\seaborn\\relational.py\u001b[0m in \u001b[0;36mscatterplot\u001b[1;34m(x, y, hue, style, size, data, palette, hue_order, hue_norm, sizes, size_order, size_norm, markers, style_order, x_bins, y_bins, units, estimator, ci, n_boot, alpha, x_jitter, y_jitter, legend, ax, **kwargs)\u001b[0m\n\u001b[0;32m    818\u001b[0m     \u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_attach\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    819\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 820\u001b[1;33m     \u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    821\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    822\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\seaborn\\relational.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(self, ax, kws)\u001b[0m\n\u001b[0;32m    606\u001b[0m         )\n\u001b[0;32m    607\u001b[0m         \u001b[0mscout_x\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mscout_y\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfull\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscout_size\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnan\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 608\u001b[1;33m         \u001b[0mscout\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mscout_x\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mscout_y\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkws\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    609\u001b[0m         \u001b[0ms\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkws\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"s\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mscout\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_sizes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    610\u001b[0m         \u001b[0mc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkws\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"c\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mscout\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_facecolors\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\matplotlib\\__init__.py\u001b[0m in \u001b[0;36minner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1429\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1430\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1431\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1432\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1433\u001b[0m         \u001b[0mbound\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0max\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(*inner_args, **inner_kwargs)\u001b[0m\n\u001b[0;32m    409\u001b[0m                          \u001b[1;32melse\u001b[0m \u001b[0mdeprecation_addendum\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    410\u001b[0m                 **kwargs)\n\u001b[1;32m--> 411\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minner_args\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0minner_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    412\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    413\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\matplotlib\\axes\\_axes.py\u001b[0m in \u001b[0;36mscatter\u001b[1;34m(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, **kwargs)\u001b[0m\n\u001b[0;32m   4496\u001b[0m                 )\n\u001b[0;32m   4497\u001b[0m         \u001b[0mcollection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mset_transform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmtransforms\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIdentityTransform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 4498\u001b[1;33m         \u001b[0mcollection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   4499\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   4500\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcolors\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\soft\\python\\lib\\site-packages\\matplotlib\\artist.py\u001b[0m in \u001b[0;36mupdate\u001b[1;34m(self, props)\u001b[0m\n\u001b[0;32m    994\u001b[0m                     \u001b[0mfunc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34mf\"set_{k}\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    995\u001b[0m                     \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mcallable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 996\u001b[1;33m                         raise AttributeError(f\"{type(self).__name__!r} object \"\n\u001b[0m\u001b[0;32m    997\u001b[0m                                              f\"has no property {k!r}\")\n\u001b[0;32m    998\u001b[0m                     \u001b[0mret\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'PathCollection' object has no property 'stat_func'"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(\"x\", \"y\", data=df, kind=\"scatter\", stat_func=None, color=\"r\", size=10, ratio=5, space=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 绘制二维直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sherwin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/sherwin/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x1a26bdfdd8>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(\"x\", \"y\", data=df, kind=\"hex\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 绘制核密度估计图形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x1a26e4feb8>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(\"x\", \"y\", data=df, kind=\"kde\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制成对的双变量分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset = sns.load_dataset(\"iris\")\n",
    "\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a27970da0>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(dataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 类别散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = sns.load_dataset(\"tips\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a28835e10>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x=\"day\", y=\"total_bill\", data=data, hue=\"time\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a28972a90>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x=\"day\", y=\"total_bill\", data=data, hue=\"time\", jitter=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a28a24b70>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6Phpqe5hSnExUzGAffkpGFNkFcRwemL55Qs2RThx29+dfalwSLf0RykqOZMWcdDbt9//xU+L0nD8vM8RRCYJf/GVXoIqLw1ZZiSYri5hVq0MdUljwen2s/ddB2pr6AYhN0HPFzbM5fqyHuqNd+Lw+Kva3olQFt5flchlyeXhUMRWzd85SW48Vs81NQXp02PzRBUE4tbqjXax7qyLoXNnKfI7sb6W/zx44N2NOGpUH2/D5/Olz7uIsFi7PG9NYhyNm74yi1HgDqaIbXxhHPP39dDz/V6xHKtBkZpHyjdvQZIq70DPhcAztounrtgYlfIC+Hhtfu3MBzfV9xCUawqoGv+jTF4QJpvPll7AeKgevF2f9cdqe+VOoQwobuYUJaHWDbWGlUk5RScqQu/ioGC1RMTqmz04Lq4QPX9DSb21tHfbitLS0rzQYQRDOnqM2eCMQV3sbXosFRUREiCIKHzq9mqu+XsrhfS14vT6mz0ojITmCRSvy2LGpDp9PIiZOx7wlOaEOdcSGTfo333zzaR+TyWSsX7/+Kw9IEISzo83Px7KnN3CsSkkRCf9LiI7VsWRVQdC5WQsymVKcjNXsJD4pAplMhtPhpvZoF3KZjLypiag1SiwmBwd2NmG1OJkyI5ncKeNvJbQYyBWECcbT30/73/6KrbICTVo6ybfejjYrGwCvxYK1/CCKqEj004uRiY1/RsRuc/H683uxmPwFF6NjdVx1yxzeeGFf0G5cF1w5g7ypY5/4RzyQ+9BDDw37wk888cRpH/N6vTz88MMcP34chULBE088gSRJPPjgg8hkMgoLC/npT3+KfAJ86HyShFwmZu4I44MyOpqkG2+m7X+fxtnYQNuf/0jKt76NwhBB4y8ew2fx7/FsmDmL9HvuD3G044/N4qTqUDs+n0RRSUqg1o7N6sJicpCQHMmxwx2BhA/Q32dn/46mIdsvHqvoCEnSH86wSX/BggUjfuGNGzcC8K9//YudO3cGkv59993HwoULefTRR1m/fj3nnXfeiN8j1LZXtPPqhhqsDjdlM1K45YKpKBXh/yUmhL/Of76Is7EBAHdXF+1/eRb9jBmBhA9gLT+Iva4OXd74mWoYag67m9f/vher2b/avnx3M9fdNo+ayk52fnocn08iOlZH3tShdbaU6qGrdw0R6lGP+csaNukvXbqUxMTELxzQPZXVq1ezYsUKwD8gnJCQwKZNmwJfJMuXL2fr1q1hm/R7TQ6ee68S78A83c/K20hPMHD+gqwQRyYIBBL+Ce6uTry23CHPk1zOIecms7qjXYGED/4tECv2t3JgZ1NgTn5/nx2z0YFOr8I+sEeuIVLDzHnpOB1uDu3xL9iMjNYye+H4ywfDJv2HH36YZ555hptvvhmZTMbJ3f9nMpCrVCp54IEH+Pjjj3nqqafYuHEjsoFuEIPBgNk8fJ99bKwepXJ81gqp7bAEEv4JLb32YfvSBGGs9M2dTdemzYHjiMJCcq+6jMN79wQKr+mzs8haXCrq8ZwkJkY/5JxarQwk/BM8Hh/f+dEKyvc0I5fLmDkvA0OEhoyvxbFs1RTMJgdZuXEoxuGd/7BJ/5lnngFgw4YNI36DJ598kh/+8Idcd911OJ2DrQqr1UpUVNQwV0Jfn23E7zvaEgwqlAoZnpM2TM9OMojB57NQ19/A9tZd6JQ6VmQuIU4bG+qQwoKrs5Ouf72Es7kJ/Yxikq7/GlFXXY/D6cFWeQRtVjaJN96MMyGRzB8/gnnnDhSRUUQvP4fu3vH7fywUEtMiiU3Q09ft/71ERmspmpVC5aE2+nsHF2hl5cfhcLqZUuLfItFmd2GzD9whyCAiWkNvr3XM4z/hrDdRMZvNPP300+zatQulUsnixYv59re/jU43dBPhE95++206Ojr49re/jcVi4bLLLiM7O5vvfOc7gT79RYsWcdFFF532NcZ7At1f3cXrm2oxWV0snZnKtSsKRCmGEao3NfKbvX/CJ/lL1EarI3l00f9DqxRFwr5Iw38+grNpcL/m6OXnkPz1W0MYUXhzu70cP9aNzyeRNyUBtUaJud/B3m0NmIx28ouSmDFnfK9ROuukf88995CRkcHll1+OJEm88cYb9PX18etf//q019hsNh566CG6u7vxeDzccccd5Ofn88gjj+B2u8nLy+Oxxx5DMcyt5XhP+i63l51HOjDb3cwvSiIx5vRfgsLwXjn6NptbtgWdu734ZuYmzQxRROHBYzZRd/89QeeU8fHkPfmbEEU0MbU1Gdm6vgaT0UF+USJLVheM265n+Apq7zQ0NPDUU08Fjn/yk59w6aWXDnuNXq/n97///ZDz//jHP87kLcc9nyTxy5f3U9dqAmDt1np+fEspmUliEcxIGFRD+1IjVIYQRBJeFIYIlLFxePoGF2NpMrOwVx/D53ajn1oU1GfvqK/H0ViPfmoR6uSUUIQcdjxuLx++eRiH3QPAkQNt6AxqFiwbOjAeDs5olCE3N5d9+/YFjquqqsjJyRmtmMJCdZMxkPABnG4vG/Y1hzCi8LY8o4wE3WDlupKEaRTGiKmEX0Qml5Ny+x0o4+IA0GRl4zVbaHrycVp++ysa/uuneG3+vuXeD96n8bGf0fnC89Q/8mPMe3aHMPLw0dttDST8E1objSGK5uwN29JfuXKlf7mx08m6devIy8tDoVBQW1tLdnb2WMUYNmRigdaIRakjeWThf3C0rwadUktedE6oQwob+qJp5P7i1/hsNuw11bT+cfAO29XSjGnLFmJWrqL3vX8PXuTz0bP2HSLnzQ9BxOElJk6PSq3A7RrcbjIpNXxn6Q2b9F988cUvfIGKigpmzJjxlQUULgozYyhIj6amxb/ZgkatYOXc9BBHFd6UciUz4otCHUZYksnlKCIi8JpNQx7zWsxIkg+fO7hssOQUc/TPhFqjZPVl0/jso2qsZic5hQlhXXDtrGvvXHnllbz11ltfVTxBxtNArsXuZndVJwq5jPlFSeg0StweL7urOjHb3MybmkR8tPaLX0g4rT3t+9nSuhOdUseanJVkR4ka8F+W12zm+MMP4rP6u3RkSiVJ37gVmQTWyiOYt28NPDfh2uuJu+DCUIUadiRJwueTxuXc+88b1U1UxnG9tq+MyeriP5/fTZ/Z3zL6YEcDj35zPi1dVrYeasds88/PvUCsxh2xIz1H+duRlwPHx/pq+M+yB4lQi8Hc4UheLz6HA4XB/3tSREaS9eNHMK7/BJ/bhc/hoOOv/+d/slpN3MWX4nM40E+bTsTsOSGMPPxYLS5k+FffhrOzTvqToR972+H2QMIH6Oizs+1wG298WodjoJ/vlQ01ROpVLC5ODVWYYe1A1+GgY4fXSVXvMealiMR0OpYD++l48Xm8/f3oCqeQ+p3voYyORp2cQtKNN+MxGqn70UkF1VwunM1NpN99X+iCDkM+n8SG9yqprugEYGpxMudeXBS2uW/836eMA6e6m2nrsQUS/gnltT1jFdKEk6gbuudkon5oUSvBz+d00v7c/+Ht948p2auP0f3W64B/ha69uhqvww6f++z6HP4qkP2bP6X2P+6j5u676H7z9Ulxxz5SdUe7Agkf4OjhDuqru0MY0dkRe+SegbLiFNbtasQ0UFwpPkrLspmpbNzXwsn/VdITxRz9kVqWXkZFTxXVxjpkyDg3c6no0x+Gu6cHny24hIKzqYmuV/9F38frQJJQJSejLZyCo/pY4Dkx55yLs6WFjhefD3wh9L7/LpqMTCIXLBzLHyFs9J+iVIWx136KZ4YH0ad/BmIiNPznbQvYXtGBQi6jrDiFCJ2Ka88t4O0tdbjcPkry4jlvXkaoQw1bWqWG++Z+h05bFxqFhmjN8HWZJjt1SgrK+Hg8PYN3l9rsbPo++jBw7O7oQD+9mMi5pbg6O9EVFGCYORPzrl1D7gDsNdUi6Z9GdkE8u7fUB35lMhlk5w+9Mw0Xw87e2b17+MUb8+fPp6mpiczM0WmRjafZO6fjcHlwun1EG8Zf3WxhYnM2+1v2rvZ2IubMxVBcQsvvfxv0nIjSeSTf/A1a/vh7HLU1yNRqYlafR98H7wcl/tQ77xJJfxj11d0c3N2M1+MjMSWCgmlJpGbGhDqs0xpx7Z1bbrnl9BfKZLzwwgtnF9kXCIekLwjjheTxcPzHD+DpHWz9p373bhzVx/xdPicoFCRcdQ19H61DcjmJOXcV8VdeHbYDk2OlobaHD984HCizPGdRJotW5H/hdZUH26gqb0OjUzFvSTZJqaN/FzviKZtnsjhLEITQcfd00/fxOrxWK9FLlpH5owfp/fA9XG1tqNPT0WZnY/rs0+CLvF60uXnk/+Z3oQk6TO3d1hBUV//g7mbmlmWj1gym0aOH26mr6iIyRsvcRVm0t5jY9MHRwONtTUZuvmsRGq1qTGM/2Rn16R84cIBnnnkGm802sEDBR2tr61nV2RcE4ez4nE6afvFzPH19AJh3bCfjRw+ijI2j/9NN2I8dpX/zp0QvPyfoOkVkFNrc8CwWNhYkSaLuaDdd7WbSs2PIzPXXNfK6fcHP80lBXwKVB9uCEnxLg5GE5ODJHS6nl5YGY0j3zT2jKZs//vGPWb16NV6vl5tuuonk5GRWr1492rGNOyari51HOmjsEN1OQujZjlQEEj4AkoRpy2f0vv/u4DmvF8fx4yRccx2arGwMs2aT8YMfIleJMajT2b6hlo/ermD/jkbefaWc8j3+QorFpcFlVgqmJ6HVDbbYj1V0BD3e22VFfYp9c2PihlaUHUtn1NJXq9VcffXVtLS0EBUVxS9/+csvLK080VQ3G/ntKwdxuv1z8y9ZnMNVy0UVSCF0FKfYeU4eYUA6RY2duDUXEbfm9BsWTTYmo51tG2rp6bSQlRfHohX5qNQKvF4fh/cH7wlevruZaTNTcLk85BbGI1fIycqLI78okf07Gmlr6ic5PQq9IbjLRi6XUTIvnd4uK61N/cjlMuYsyiIuMbSrzM8o6Ws0GoxGI7m5uRw8eJCysjK8Xu8XXziB/HtrfSDhg78Uw/nzM4nQha5vTpjcdPkFRC5YiHnXTgBUScnEXXAh3n4T5p3bA8+LPndl4N/26mOY9+1FnZhI1NLlyNWTs8W/7q0KujssABze14oELD9/CuBP1idnN7lCxvuvHaK1qT9wrnBGMts31VGxz/8F0VDbQ05hPIZINVazC5kMSpdkExNn4PKb5mAy2lGpFej0of99n1HS/+Y3v8n999/PH/7wB6699lrWrl1LcXHxaMc2rtgcwfW0vT6J420mNu1vwWx3s7QkleWzxvcWasLEk3rnXUQvXY5x0wZ8bjeWAwdIufV2dFOmYj1cjkypRBUbiyRJWPbvo+3PfwxM1bQcPEDG/T8M8U8w9mxWVyDhn9BY69+ERqGQM2dhJrs+qw88NrU4hV2bjwc9v2J/Kx0t/UHnGmt7uf0HS+lsNRMRpSEqRofN4qS320ZSamTQgG8onVEUixcvZs2aNchkMt544w3q6+uJjAzfetIjcc7sNI63DZatnZ4Ty7P/rsA68GVQ09yPTqNkflFSqEIUJqnut9/AUVcHgO1QOZLLiUytxrrfv/GRZfcuYs+7AGdzU9DcfFvFYVwd7ZNuBy2tTok+Qo3N4gqci080YDLaUSjllC7JIS0rhq52C2lZMag1iiFJX6VSYIjQ4HIOrtbVR6hRKhWkZfnn71eVt/Hph8fw+STUGgUXXVMyLub2DzuQ29bWRmtrKzfddBPt7e20trZiNBqJjIzkjjvuGKsYx4Xls9K4++oSls9K5bpzCzhndnog4Z+w71hXiKITJitXV2cg4Z9g2rkjaGUugHHjelB+ro0nkyGbhAO6crmclRcXoR9YUBmXaMDl9vLS/+7kxae3s3ndMVIzY5g5P4OE5AiiYnRMmzVYSFGlVjBnUSZlK/NRqvwpVKGUs2RVQeA5Xq+PbRtqA7N7XE4vOz4N/juFyrAt/aeeeoqdO3fS2dnJTTfdNHiRUsmKFStGO7ZxZ05hInMK/VOt2nqsQx5PjhUbowtjS2GIQKZSBQ3eKmNjcQ8UVguQy4m94ELsR6uQXP4WbvSyc1ANbLM42WTmxnHL9xZht7mpr+5h8zp/fSJJ8nfd5Bclkp4dG3j+igunMmXKW+jeAAAgAElEQVRGMqZ+B1l5cegNamxWFzd9ZyG9XTbikwy0NfXz7qvlaDRKiuem4fxco9BqdjEenNEmKs8++yx33nnnWMQTZLyvyH37szre296A1ydRkBHNfdfMRB/CRRfC5NT38Tq6XnsFfD4U0dFk3P9DnI2NtP/tL4HunLhLLiXhiqtx9/VhO1SOKikJfdG0EEc+PmzbUMPBXcH7Wy9dXYDJ6KClsY/ElEgWrcgLDMJazE7WvXmYzjYzWr2KFWumoFIrWfuvg4Hr1RolyemRNNUNTqktXZzNguVjsz5ixGUYTrDZbDz99NNs374dr9fLokWLuPfee9HrR3e+6XhK+jXN/Wzc34JaJWf1vEzSEwx4vD62H26n1+xkxew0oiPCe3OFsWRymanoriJOG8uU2HxRAuAsufv6cHd1os3NDczBdzTUY6uqRJuVjX7a9CHX+BwOUCiQqyZ3Q6W1ycg7Lx0IHCuUcnIK4qmtGuyuzciJ5dIbZgGwfm1l0Jx8tUZJ3tQEqsrbg1733IumYjI66O60kJkTS3Fp+ph9zs866T/00EPodDquu+46AF599VXMZjO/+tWvvrooT2G8JP3GDjP//fc9eAf65/QaJT+/YyHPrj1CZUNf4NxPvl5KarzY6emLNJqb+d2+/8Xp9d/uLkwp5evTr8ftdVPZewydUkdBTK74IjhDks+H5HIh157Zdp2Sx0P735/DvHMHcrWa+MuuIPb8NaMc5fhWW9XJ4b0tKFQK5i7KYt1bFTjswesd7viPZShVCl59bjc9ncHdu7MWZAy5W7jq63NJTgtNtdiz3i6xoqKCf//734HjRx99lIsumjwLPXZVdgYSPoDN6eGj3U2BhH/i3Cd7m7nl/KmhCDGsfNLwaSDhA+xs38vStEU8f+Sf9Dj8v9MZ8UXcNfNWkfi/gOXAfjr+8Xe8RiP6GcWk3vEdFBHD7+vQv3kT5u3bAH9rv+vVf6GfUYImPX3Y6yay/KIk8k+aeRcTr6e9eXBKZmS0FrPJgcXkJCM7NijpR8fqmLs4m/ZmEx2t/hl+0+ekhSzhf5EzSvqSJGEymYgaWAFoMplQKIYuL56oTlU2WXeK5dVer2/IOWEol2/ogNaO9t2BhA9Q0VPFsb5apsYVDHmu4OdzOmn/67P47P4NPWwVh+l+503iLryY7tdfxdnchH5GCQlXXh20CMvR1DjktZzNjZM66X/e0tUFfPjmYSwmJ1qdiuT0SP71f/5S8zq9iqklybQ3m4iJ01G2Mh+tVsVVX59LT6cFlVpBVMz4ndRxRkn/1ltv5ZprrmHlypVIksTGjRtDMrAbKktnprLtcDsNAzV3ZubHs2ZhNnuOddE4sMhDpZSzYo74T3MmlqWXcbi7Cmlg37H86BwUsqEfRZsnfHcnGgvuzo5Awj/B2dBA65/+iLPeP6/c1doKXi9JN96MJEl4errRTZmK6bPNgWtkSiW6QnGHerLElEhu+s4iTEY7crmMfz6zM/CY3eZG8sGN3x66/0B80vjfPe+Mkv7GjRt5+umn2bVrF5Ik8Yc//IHHH3+ca665ZrTjGxd0GiWPfHMeNc39qJRycgfqYT9w41y2HW7HbHOxcHqy6M8/QzPii/hB6XfZ31lOnDaWstT5dNg62dq6E6/kXwAfo4lmerxIRMNRp6ahiI7B228MnNPm5WP85KOg51nLD+JafT6tf/wdrtZW5AYDkWVLcNRUI9frib/8ikk5ddNictDZZiYpLYqIyKGTMORyGTFxero7LJ/faAyrxXlG72Hud3BoTzNOp4dpM1NJyYj+KkI/K8MO5H7/+9+nsrKSzs5OkpKSAlsj+nw+UlNTefnll0c1uPEykCuMjXpTI9vb9qBX6lieXkasNvSrF8c7R/1xul55GVdnJxFzS0m4+lrqf/z/8JoGV48bZs5CplRi2bc3cE4eEUHer/5n0s7cOVbRwcb3qvD5JORyGasvmxbUp38ySZJ47W97gvrxV15cxNSS4Vcyu10eXn52F9aBlb9yuYwrbp4zJn39I569Y7FYMBqN/PznP+fhhx8OnFcqlcTHx6P8/Aq/r9h4T/oHarp5fVMtZpuLpSWpXL0iH7kYeBwxt89D1Umzd4SRsZQfpOO5v+C1mFGnpJL2/Xtp/ePvcbW3BT0v95e/QRUXvnu9no0Xnt4WtFgqKkbLTd9ZdNrn26wuDu5qwmR0kF+USMG0U39BmIx2utrNJKdF0dFq5qO3K4IenzE3LVDYbTSNePZOREQEERER/PnPf/7Kgwp3JquLP711GM/A4O0HOxtJiNFxrujXHxGTy8xv9jxNt8Nf+Ko4vojviNk7IxIxcxaaR35G+9/+gr2mmva//QVtfn5Q0tdkZp51wve53ciUyrD8Gznsns8du6k72sXebQ14PD5KStMpnjv4f1mrU7FgeS4KxWDlmr4eK8YeO2lZ0Wi0KqoOtbPp/Sokyd+qn1uWPeR9deOgKu/4KPs2jrk9Xg7W9CCTyZiZH49K6f+j17b2BxL+CUcb+0TSH6HNzdsCCR/gcE8V1cZapsRO3Nk77p4eul75J87GRvTTp5Nw7Q0odP5ZH167HblWO+KE2vXqy9irKgFw1NbgdTiIXXMR1vKDqNPSSbzm2jN+LZ/TibO5CXVaOgqdDq/dTvtfn8V68ADK2FiSbryFiNlzRhRnqBTNTAmURQbILUzgo7crAn33n31UTVSMjqy8OA7ubmLPlga8Hi/TZqWx9LwC9m5rYPdAJU61RsEl189ix6bawPU+n8SxinZyCuOpr/bvWRwVo2XG3NDnB5H0h2F3enjshT209fgr6WUkGvjJLfPQqBVkJ0cil8nwndQ7dmKAt6alH4vdzYycWFTKyTO19WxY3UNn6ljctlM8c+Joe+ZPOOpqAejf/CmS10f8ZZcPnK9DlZhIym13oCucgsdswnpgP4roaAzFM5HJ/Y0Pj9GI5PWiig9utdurjwUdu1uaiXvwJyRec92wMdmOHcXV1op+2gzUSUnYjh2l9Y9P4bNZkWk0pH7r29iPHcV6YL///Xt7afu/Z8j/zf8g147faYqft3R1AbHxejpaTAODqxJHDwfvfNV8vBe9Qc229bWBc4f3tRAbr2fvtobAOZfTy+4tx4fU2nE6PFx4dQntLf04HR4ycmKD7hRCRST9YeyoaA8kfIDmLiu7KjtYNiuNuCgtt15UxGubarHa3ZTNSGFVaQZ/evswe6o6AYiP0vDQzaXERZ3ZSsnJbFFqKVtad+CT/HdPMZpoZsQXhTiq0eO12QIJ/wTr4UN4bdZA1Ux3Vxdtf3mGtLvvp/mXj+Oz+T+LhpmzSLv7PjpffJ7+zzaDJBExt5TUO+9CNjDOps0vCJRWBlCnpQXuIk68v2nLZ3hM/UQtXIQmM4uu11+l78P3/U9QKEj//r10v/UGPpt/AFNyOul8+R+oEoL3d5WcDlxtbWhzw2cnOblcTklpBiWl/uP2z9XGB//0y85205DznW0mfN7goVCn3UPRzFSOnLTr1onKnCnpoZ+xczLFz372s5991S/qdrt58MEHef7553n55ZeJj49HoVBw11138eabb1JeXs4555zzhbeuNltoq9IdbTRSUd8bdG5aTiz5af4/YkZiBEmxOjKTIlk+O40uo51XNtQEnmt3epHLZczInXzT4b6sGE000+KmIJPJKIot5Maiq4lQT9wpsDKFAtP2rYFEDqArKMDV3Bw0995nt+NzOXCeVD7Z3dGBwhBB73trA+dcbW2oEhPRZvn7kXWFU3A1N+Hu6UadkYmhZBbOpkZUCQnI1BqanngM0/atOGqq6d+yGW1ePp0v/2Ow3r4k4e7pxt3VGajKCf4VvFGLyoLuJOQRESRccy2yMF6wGTHQMOscWFGbXRBPWmYMsQkGjhwI3j5x3pIc7DY35v7BSqalS7IpXZyNXq9Gq1NRPC+dOQuzQjbeYTCcvg7YqCT9t99+G4vFwu9//3vOO+88vvvd71JVVcVdd93Fvffey8aNG/F6veTn5w/7OqFO+nFRGrYeasPt8bc+I3Qqbjl/Clq1vzX17NojvPXZcY409PHpgRYSorVBpRkAUuL1gXLMwvBitdGUJEynKK4QnXJi3x3JZDI0mVnYKo/gc9hRp2eQcuu38BiNOE9aMavOyEQZFY2ruSnoelVKStAXAYA6JRVHbQ1dr7yMs+E4iTfcSMIVV2Fc/wnW8gPYjlRg2rYNZUIi/Rs+GbxQkpA8HlytLUGvp4iIxDCjJLDQCyBibimJX7sJr9WKp7sbdVo6qbfegTox/DcPSs+KYdb8DPp7bdQd66b6SCdNx3tZsDyX/j47CoWcabNSmTU/k7wpCahUcvSRakoXZ1NUkopMJiMpLYq8qYkkpkSGdIB7uKQ/Kt07a9as4YILLggcKxQKKioqWLBgAQDLly9n69atnHfeecO+TmysHmUI+8QTEyP53Q9W8NHOBsw2F7XN/Tz47A5mFiRww3lT2XlksA/Q45U43m4hKU5PZ6+/9SaXy7hkWf6w06eESSxxPlllc3Gbzahj/GsSkvPuoE6twHjgAIacHPLuvB13v4nDu3chefx9xoa8XPKuuowDmzYGziGTofa56HjH3z3jbGzA09ZC+tVX4e7qDLyl12JGqq/h8wzxMWiXLaF785bAucwrLiFx+TKaUxMxHa4gorCAjGuvQanXkXz/90brtxJSLY1Gak6qrmkyOvC6JZacW8BH/66gfHczHS0mbvzWQtZcURLCSEduVJK+weC/LbdYLNxzzz3cd999PPnkk4FvPoPBgNn8xXPw+/rGdiCvqdPC/uoukmJ1zC9KQiGXowAunJ/Jz57bRWOnv+TC7iMd2G3uIde7XB4e+NocPtnbhMXmZklJKkmR6nG/3kAINQWc9BmJvembxA7sWWQBSIgk6yePYtq5A2VUNFHLlmNV60i/9wf0fvg+kttNzOrz6X3/3aBXtTe3YGwJHpwE8OgjMZTMxHqoHAC53oBu6QpUiUko8qbgamnBMHMW8mnT6TE60K26EN2qCwHos3rAOnE/z20txiHnOtv72bG5NtCP39FqYt2/D3POmvG7Yvysq2yORFtbG9/73ve48cYbufTSS4PKMFut1kDxtvGivLaHp14vD8zG2Xesm+9e4d/83e70BBL+CQ2dZuYUJrC/uhsAuUzGefMziY3UcO2K008z7DM7aemykJcWjV4rxtGFM6PJzCIxMyvonH7a9KA6+Za9e4K6YmQaLVFlizFt+SwwR18RHU30kmXEXXgx1sPleE0mDLNmo4z0/3+MXrp8DH6a8Ss9OwZDpAarebDMQlpWLDWVwVuhGnvDty7UqGSd7u5ubrvtNh599FHKysoAmD59Ojt37mThwoVs3ryZRYtOv/otFD7e3Rg0/XJPVSfdRjsJMTp0GiXpCQZaugeXYeelRnHXFcXsrurkSH0vfWYnO490EG1Qk5Ucya7KDl7ZUIPF7m/x37i6kO0V7bzw4VG8PgmNWsF918xkalbsqcIRhC8t4cqrcDY14mptQabREjG3lKZfPI4kg6gly9Dm5BA5bwGKSH8rMGLm7BBHPP4oVQquvHkO5bubcdjdTC1JIS0rmv07GoMGbnMKw3cl8xltovJlPfbYY3zwwQfk5Q1O4frJT37CY489htvtJi8vj8cee+wLyzOPZbfIb185wOHjwTN1nrhzEf1WFwnRWix2N8+9X0ljh4W8tChuOm8KualRNLSbeeyFwQ1WtGoFD944h/9+YW9QDf7rzy3g3e31QZup56VF8fDX543JzyeMT5LPh72mGplShS7v7Kc8SpKEu7MDV0cHrU/9z+ADMhlZD/8UbXbOiF7X53Yhud0o9IZA3OZdO3A2N2MomYl+anhNr22u72P3lnpcTg/TZ6VSMi8j6PH+Phv9fXZSM2JQqRUYe23s2nwcc7+DvKJEZi/IHNcrkc9656xQGcukX3G8l9+9djCQqGfmx9PYYcZocSGXybhmRT6rSjP489uHOFDTg0wG58xKQ6dR8sHO4Prk585JY+P+4GlepVMS2Hesm5N/2fFRWn713cWj/aMJ45TPYafpl7/A2ehf6KMvLiH9nvsDC6/ORvfbb9D77tqgcwnXXk/cBRd+6dfq+2gd3e+8heRyEjG3lJRv3UnnP17EtPWzwHOSb72d6CXLzjrusWC1OHnpf3fi9QyuqL/gyhnkTfXPstuztT6w2larU3HZ12adtmSy0+Gms81MfKIB/cB2qTWVnRw73IE+Qs3csqyQ1NYPSZ9+uJmRG8d/3b6AAzXdJMXo2XGkHeNAdTyfJPHm5joUchkHavxLqiUJNh1o5dxTLKsuyIjhs/I2PCct4CjKjkNCxr5jg32DZcXDV+kTJrb+LVsCCR/AdvgQ1vKDIPnoW/8JMqWSuAsvDrSi7dXVeC0m9NOLkWv8CcZrs+Jqa0OTlRXYGxc4ZYv+xDlHYwM9a9/BZ7EQtWQZ0UsHk7UkSdirKvEYjRhKZuK1mOl6dbCarmXvHvoyszBt2xL02sZPPg6bpN/aaAxK+ACNdb3kTU3EbnOxd+vg38Rhd7N7Sz3nrJnCwV3N/pb+1ETyixJpru/jgzcO4XH7kMtlnHtxEQqFjI/fORK4vul4Lzd+e+G4WIl7gkj6J0mNNwRq4n+4qyHoMY/XR3OXZcg1yTE68tOjqG3xL+oonZLIwunJqJVyXttYi9nuYklxKufOSWdpSSrrdjXS0GFmRm6c2HRlkvOahq4CtddW0/fhB4FFUvaqSnIee4Ku117BsncPAMrYWDIf/AmO43W0P/cXJJcLRUQkaffchy4vH2dzk7/Ucuk8/5eITEbsBReiL5qG126n+de/DKyytVcfQ67TEVnq72Zse+ZPWPb4d4iS6w3EXXrZkBhdLS3IFIrB6aIQWAkcDuIShi76O3HO6fDg8wV3ftitLt59pZzugQ2Taio7WXXpNA7uasLj9n95+HwS29bXDKmXbzE5aW/uJz176Nid2+3FaXcHFoaNlfD5S42xRdNTAokcIDs5kmUz09hS3hboolEq5OSkRFKYGYMkSahVCrxeiZ+/sJeWbgsz8+L5xoVFGLT+ynoatYLLloqSwYJf5IKF9H30YSB5ynU6fE4XJ+/YIXk89G3cEEj4AJ6+Pvo+/gjzzh2B1bJei5nu114hZtVq2p75c+A1Ys47n8SrrwskZfvRqkDCP8Gyfy+RpfNwNjUGEj6Az2bFUX8cmUqF5B6comyYPRtlXBx96z7wn5DLibvokq/wN/PV6OuxYey1kZYZg+akmXLxSREsWJ7LvoGKmhk5sdQd7WTvtgay8+NITImkq32wazk9Ozao1g7A0UPt2CzBi0cddjf6iKFbq0ZEaXC7PHg8PnR6/+NVh9rZ+kk1LqeXpLRILry6BP0ptmUdDSLpn8aq0gxUSjn7jvnn7V9clkO0Qc13ryxm/d5mlAo5GpWCJ/+5Hwl/MbYf3DCbx1/YS/fAKP+eo13oNEpuvWhaaH8YYVzSZGSS8aMH6d+0EZlaRcyq83HUVvP59r9Crx9yrddsxmsOrgvj7u6m9/33gr40+jduIOHyq3B1duBqbUERPbQOjDopGfBX0/w8mc9H+j330/32m3gtFqKXLSdqYRksLMNQMhNnSzOG6TNQp6aN4DcwevZua2DXZv/0VbVGwaU3zCJpoCCizydRujibmfMycLu9vP2P/fT3+adgHj3cwdSSFDJzY+nvs5M7JYHUzBj2bW8I2j1Lp1cxpTiZAzsHV0rnFyUytyyb5vo++gemdM5emEltVRd7t/q/YHKnJLDsvAI+W3cMz0AXU2ermT1b6ll+wejX2QeR9Ie1fFYay2cFf5hLpyZROjWJ5k4Ljz63K3C+ucvKu1vrAwn/hGPNQ2/hBeEEXX4BuvzBdR2qxEQsBw/4q1jKZEQtXUbs+WswbflscGWtXE70OSvwWq3YDpcHro2cNx/rkeBNOyRJonfdB/SufQcAmVpNZNlizLt2gteLNr8Ar8tF4y9+jiYzE3VGBq7m5pPe51z0RdPIOmk9wAn6omnoi8Zfg8bpcLNna33g2F8Fs575S3PY+P5ReruspGfHsOqSaUiSFEj4J7S39FO2Io/j1d20NfUzbVYqsxdmsn+HP8Hr9CrmLs4mIkqDy+Ghr8dGRm4ssxdkolQpuOFbC+hsM6E3qHG7vbz618G7tOPHuomM1gYS/gm9XcF3X6NpUiX9xg4z6/c2IwGr5maQnTLy8gg9JseQc1aHm7goDb2mwRZTXuqXW4TW1GmhtdvKtOxYosbodk8YP+QqFenfvxd3Vxcolahi/X3BmQ/+GOPG9XhNZqLKlqArLESTkUHv2n/jaGpEP206cRdciDojg46//TXwelFlSwYrZwKSy4Wnp4e8X/0PPpsN46YNGAced9RUo5taRMLV1+Hp7yNywSJ0ecPXxxqPXE7vkCqYdpubT/5dGUjwLQ1GtnxSw3mXT8MQoQ5saQgQG2/go7ePBPr2925r4NyLi7jhW/Mx9TtIy4rBaXfzyl92Yxn4v66PUKNU+aegy+WyQGXNmspOPs/pcBMRpQlcC/4Cb2Nl0iT9bqOdJ/6xD6fbv/H2rsoO/uv2hfT0O3h9Uy0mq5PFxalcviwXn0/i0wOtNLSbmZYde8pZNkUDSdlkHfywLJyWwurSTJ7/oIrWbisl+fFcv+rUq3Obuyy8v6MBm8PDsplplE5N5J0tx3lny8AtqVLOD66fzZTMybtPrCRJmN0WIlURgTnRLq+bGmMdcdoYUgzJIY5w9KgSg4v0KaNjSLjiaiSfj9731tL5zxdQJSWTcNU1JCYPfj6jlyxDnZSMeddOFFFRRC5eimnL5qDX8tpsKKOiICoqaKwA/H3+ad+/N6gMc7iJjNaSlhVDa+NgSYX8qYns2BRcoK6zzYRMJmPBObns2dKAud9BWmY0WXmx1A+stD+htaGPopIUYgcGfHd/Vh+UtGuruuhoNZGcFkX5nmb2bWvA55OYNisVpVIe1LLPzo9n9oIsdnxah8loJ78oiVkLMkfjV3FKkybp7znaFUj4AC63j22H2li3qylwfu22emIiNRxvNbHlkH/Z+pZDbXT327l0SfAArEal4IEb5/D+jgbMNjdLS1KZXZgAwH9/ayGSJJ128YbN4eHJl/YFFmqV1/bw/StLeG97/WB8Hh/vbDnOj74WXjsSfVWazK389fCLdNl7SNTFc1vxTWgVGn6373/pd/kH2VZlLueqwvE3gDiaet9/l5533gLA2dSEs6mJnMeeCJrbbz1UjnHTBpAkTFu3oJ8+A9tJ3T7Ry5bj7u1FppCjSkzE0ze4KFERFRWYDhrOLry6mPI9zRh7bOQUJlAwLYmjh9vp6x6s55WYHMmrz+2ht8uKXCFj8ap8Zs3PHNLdA6CP1PDea+WBKZsO+9DaWw67m45WE1s/GSxod2BnEwuX59JY14vT6WHarNTABuwXXROagm2TJulHGYbuTWl3eYO+CAAq6no4WNsTdO7Tg62UFafw1ubjtPfamDslgQsXZpMab+D2i4P7Ojfub2HdrkZkMhmXlGWzpCSV/ce6eHl9NUaLk0XTU5iRGxu0Mhdgd1VH0Lx+8H85TFQNpiZer15Lt72H2YklXFV4CSr54Mfxn1Wv02X3/x267D38s+oN0g2pgYQPsKHpM87JWEy8buLuV+Bzu0GSkKv9XX3W8gNBj7s7O/zz9NP903/dXV30fjA4mOvu7kJXNI2Ea6/H1dKCfkYxlv176Xr5JZDJiJg9F0V0NN7+fmQaLUk3ff20i8M8RiPu3l60OTlfyQKy0aTWKJm3JCfo3PmXz+DTdcfo6bSQkROLUqUI9KX7vBI7NtUxZUYy0bE6zlkzhZ2f1uFyeimckczRQ23YLP5Ev7e7gelzUpHJBsfMI6M0ZGTHcnhfcHlq8E/NvOLm8dN4mzRJf35RMpsPtAYGVgsyolk5J531e5qDau5kpURS1WjE5hxMuHqNkt+9Vk7rQO2d420mJAkuWZwT9B5HG/t4cd3RwPFz71USH6XlmX9X4Bq4vdtyqA2lcugdQGqCgVn58UFfOOfMHl8zIr4qHp+HP5f/DbPLP+95c8s2DCodl+QNluNutbQFXdNiaSNKHTwGIyFhcVsnbNLvfuct/7RIn4/oc84l8YYb/TXzT6qjL1OrUURG4LVaURgMePqNQbN3wL8eIO6btwFg2rZ1cFqmJGHZv5e0u+9DGRuLOikJuVaHva5uYCqpm5iVqzFMn0Hvh+/T/dYb4PWiSkwk/Qc/Crsa+nGJBq48Kfm+89L+oMd9XgmLyYlOr2b67DSmzUrF55Po6bRw9FB70HON3TYu+9psjh5ux+eVcDrcfPzOEdJzhnbHToqds74qX+UmKgq5jCUlqRTnxrN0ZiqXL8klQq8mJlJDdbMRj9dH6dRErju3AINWxeG6nsB1ly7JYevn/uh2p4ekWD3Prq3g/R0N2F1eOnptHGsKnq2jVMipawueWhdlUDM9N46GNn+rNTslkpvPn8KC6clE6FTERWq4bEnuhF2x22JpY0PTZ0HnfJKP6fFT2da6izZrJ26fO9DSB5gRP5WFKXPZ33UocC7VkMwleeeP6xooI2U7WuUfkPV6wefDcbwOTXo6UWVLsFdV4jWZkGv9RdW6/vkPet/9N47GBqKXr8CyZ3fQXPzoFStxtjSD5F+M9fn9c7V5+UTOmYtMqcLd20PjY/+Jq6kRd3s75p070OYX0PH8c/5YAJ/Nhs9uJ2LO3DH9nXzVXE4vTSfV24qM1qIzqKjY14rT4SEhOQK5XI5SJad8TwvSSYu2sgriKZ6bTmJyBJ99XE1ft39NQHN9H7MWZNJv9G+6UlqWxbQQNN7GfBOV8Uomk1HwuRVzy2elsbg4BY/XF9gRa1VpBtNzYmnssDAlMwatWsFrG2uDuoLio7T8/vWDuAZW5L21uY6VpUNX2M7Mj2P7kfbA81Eu7M0AACAASURBVAAKM6K5uCyHNQuysDk8ZCUPDlResCBryGtMNIm6BLQKDQ7v4EBYvDaOx3b+FrvH35+aakhmXtJsjpsayI3O5prCy4hUR6CUK9nbcZA4bSwrs5Yhl43vboaROrk8w+C5RvTTi0n51reRKZVIPi8Njz4caNlbD+zHuOETMn70AL0fvIenrw9VQiLdr70CPv/nL/rclQT1SygUGEoG+5atBw8EbY+IzxeY3nkyd0/wQGc4KpmXjs8nUXe0i8gYLV63l+0b/HdRxyo6MPc7WLA8F5VayaJzcgcKtHlJTo8KdB3VV/cEVuWCfw2AXCHjm3cvCcWPdEYmVdI/HaVCjvJztTFOLskAcON5hbz08TFcbh/JcXpm5Max91hwjW2z1cUFCzLZsK8FmQzWLMhizpQkvnuFnJfX12C0OCmbnhxI7IkhKMQ0HmiVGr4x/Qb+dfQt+l0mpsdNRafQBhI+QJu1gyvyL+LW4huDrp2VWMysxOKxDnnM6YumBydnQPJ6qfvhfUguF6qkZGIvuHBIV46zuQlVXDzJN30dgPqfPhxI+ACmbdtIvfM7GDduQKZQEL1yNT1vv4ll/z5UKalELSobEosmJxdVzTHc7YN3u5HzF3zVP/KYk8lkzF6YyeyFmXg9Pv7y2+C7z6pDbWTkxrJ+bSUWk5OYeB1rrp5C+kA5dLfLS0TU0BZ15EBZBafDTU+nlYTkCNSa8ZNqx08k49yymWmUTkmiz+IkNV5PT7/j8/8nyUqO5OKyHK5ano9MRuCLZGZ+AjPzE0IU+fg0M3EGxQnTcPs8aBRq3qx+9/+3d+fxUZbnwsd/s2a2JJPJvi8QIAtbCISALCKLUKItClZb6SKH9/Q9rZW+rfqec6qttmqrPb6V1i62thW7uSJiWZS9CIRF1oSQQHayTLbJTDL7PO8fA5MMCUoVmCz39/Px8/F55pnhnknmyvPcz31d14BjJIZsAdgbLiw1lYQ1a+l4710krxfj/AW0bXw7cBbubm2h59QJZGEaJGdfzojSaKT+J0/hc7uJum0hkis4y1byuNFPnkr49CIAWv+yAethf5Khq6Geju0WDAWF2I75l3JqJ+QQOWs2hkmT6Nj8Lu42M4bC6Rjnzr8Jn8LNI5PLUKkVOPstntBoVOx672xgaWZXu52j+2vR6dR8sKmctlYbphgdKZlRNFT7e2MnpxsZlxdP9TkzH2wqx+PxoVIruH1FHikZQ+Pekyit/BnsONrAW3vP43B6KRgXy5qSXE6db+fvO6uw9rqYPTGRexdmD7iKEAZq7TXz0yPrsXv8ASzZkMgjhQ+ikIeuR/JQ4mppoea/HgnaF5aWTuwX76PtrTfwWrvRT5pC1473g87sI+cvwLJ7Z9/23PnE3nsf3i4LqthYap94fMBUUsaTTwEgebyEpd689eM3k63bwYHdF+gw95CWZWLGnEwqTjezd9s5JAnkChkLS3LZvjE4w1mrUxEZpaW5X12uuMRwFiyfgM8rBUowb3jxQNA6flOsnnsemH5z3hyitPJ1sa20jveP1KNUyCmZlcHsiYnMmZSIUi7D0uukOC8Rh9PDbzadCdTk3/VRI/EmHYunj8wvzvUUp4vlv2Z8h6OtJ9AqNRTGTxUBvx91fDzqlFRcDX21XgwF09CNG0/ao/8FQNeunUEBH0Aepibpm9+mt7yMsLQ0ZOowLvyfdfh6e1AnJROWlhYU9BUREahi44ZV1cxPY+tbpzE3+1ePdZh7kHwSs24bS0pGFG0tNozROhQKOQkpETQ39AX41EwT588GZ9mam61E9ZsK9vmkoHaLwIDtUBrZP9nr5NQF/9n7ZS+/V05KnIFXt1Vw/qL/F2LLwXrumpcV1C0LoKrRIoL+NYrSGFmYNi/Uwxiykh98iPaNb+NqbkIZHY31SCnWI4cxLVlKRPEs1EkDV4moEpPQZGSgnzQZyevhwnfXBVb2uC42ooqNxTCtENvxj1DHJxB//1dGfMDvsTkDAf+ymqp2Zt02lgijlqryVt7fVIbPKxGbYCBjbDTt5h6S04xMLU7DbndTf6Fv1U9Smn+ZZlODhYpTzWi0KtLHRlNT2bf6bGzu0FneOrJ/utfJ2drOoG0J2H+yKRDwAZxuL9VN3SgVsqAkq+whtkZXGL5UpmgSvr4GR00NdT/+YeCGUvPLL6GKT0A3fgJRi2+n89IUjy5/Ih1b3qP1jy+jjDIRs+qL+HqCC3u5za1kPPFUKN5OyGi0KjRaVVBWbVS0v5Jpd5edQ3v6msubm22kFpsYMyGWfe9XcfZUM7GJ4aRmmTA3dROfFMncJdk01Xfxzl+OB+7xGSLCKChOw9xsJSnNeFPLLHwSEfQHUVbTQXltJxkJERSMiyFzkKJpCaaB5W7DVArWluTx2q4qrL1uZk9MoDg/gT9uKed0dQcpsQbuW5hNXNTA5wrQZm/ncPNxtEoNRYkFaJVa7B47h5qOYfc4mJ4whRjt8G1Ifb30lp0OXkEgSfSWnUZlikIzZixps2ajjIik6Tcv4mlpAcDT2UH722+iTk7B1dgQeKp+FDZHVyjkzF86jl3/qMDp8BAZpSU+OZLaKzLxL+sw93DycEOgfo65yUp+QRLLV00KHHP4nzVBPxJbt5OElEiK5n32vsfXmwj6V9hxtIE/v9+XvLJkRiqrbh0bWIqpVMj4XHEG8wuSOVDWHGi0EqZWsKAghZQ4A4UT+i7l/rjlLHtP+LNLO7qddFqd/PDrA5e7mbvsHDtnxmgIY9r42FF387e5p4WfHlmP0+tfnbLv4kG+N+0/eO7IL2nu9c+hvl+3i4cLvzWiC61dC3VKyoB9PoeDC49817+eXi4n4etr/AlZ/bhbW0h/8ina39mIq+ki+kmTMd2+jJZX/ojt+DHUCYnEfvE+NGnptG/eRNfOD5Cp1USX3DlsWiFeq8xxsaRmmWhqsPD+xjMc2uNfn5+SEYVGq8Rh71vFE5tgoKYq+A9Ch7kHj9tLfXUn6jBFUJOWywbbNxSMmozcy8xddn79zhn+/P45zjdaGJ9mDCRlAfz6ndNBJRjqWmwsnZlOdooRm91Nr8ODRq0gO8XIvMlJxEfpyE4x8uXF40iI1rPrWAOvbq/go8o24k06thysDXq97h4Xt05NJkzdd5OyuqmbJ/90hJPn2zlaYeZCUzezRmg27tVsq91FVVffZbXN3YMMONHWt3rCK3lRypXkRo8PwQiHDlVcPD67HUdtDcjlGBcsxPbRMXw9l+apJQn7hfPoc/P6auMD2nHjCS+cDpJExMxZGOfOo/2dt+ja+QGS04mnvZ2eU6dQmky0vvoKktOJr7eXnhPHMUyb7q/MOYLI5XJOltbTVN83Tdvd5WDOkmwA1BolBcXpTCxM4ezJJtyuvgS17Lx49m6rpOz4RSpOtyCXy0AC16VjssbHMCWEiZYiI7eflzaXUXWp/s7xqjbYCg/e3XeZppAHp/TLL21v2FbBwTL/pXJjWw8Wm4sH757E7ImJgWNLy1vYsL3vKqGywUJ2cmRQY5Wo8DDO1HSw/1QTBq2KzxVn8MGR+kBtHoAz1R3UNls/U73/4WawzFqlfOCvp0I2+lb0WPbuoWv3TuRhYZhK7kSfm0f08jtQ6PV4e3uJnDOX7gP7g57j6+nxz+G7XLjq6tBkZmIomEbNf//fQHtG422LBpRk8HS003M8uKgbkoS9siJQ1G0k6Z9Ne5lWpyZrfCw+r0TW+BgUCjnLVk7i4O7zdFscjJkQiwyw9vteN9VbWHZ3Pj4JtFrVgF65Q8moCvpeny8Q8C87W9dJS2cvWw7W0WN3M2lMNB8caQikBS0tSkOpkPNRVXDa+YnzbdhdHkrLWrD2upmRE8fxK2pw250epo6LwdLrorbZiikijHlTknnp3bLAMWeqO8jJGNg02Td00yduiDnJxRxoOkyP21/6Nj0ilYWp8zjdfpbabv8yRb1KxxhjJn+v2IhKoWRe8siusAn+Msktr/whsH3xhedJf/IpGn/+P4EMWcvunRgKCrEeOhA4Tj9xEnU/fAyvxYJcoyF8xkz/GX2/ZuZdu3YQPn1G0JJNuV6PNjd3wB8RzTBspnItcqYkcu5MS6BhSlSMjg93VtHV7s8OP7K/hru+Mg2X04O9xx34T64YWO/J4/EFyiYPZaMq6CvkctLiDNS19i3XSk8I55lXj2Hp1wzly4vH0WV1UnXRwrFzZiTJf+O2tl+z5PgoHc/99SOqLxVN23ygZtApmXGpRuZNScZmd6PTKPnDe+VBj/c4PGQkRHC8sh2P13/WMSHNOOjN45EsRmvi+0Xf5bj5FFqFhslxE3F6ncxKmM7YyExitCYS9Qn88sTvcPv8gau06RiPzfwuOtXIvTFuO3kiaFvyeOja8X5QSQTJ7Uam1RL35dXYK8+hyRqD9XApXov/BMfncNDy6iuoYq7ICvf5iLp9GR6LBfvZcpQmE/Grv4oubyKuhnp/qQaViuiSz6NJS7/h7zUUEpIjuesr06gsa0GrU6FSK9i7rTLwuK3bSfmJJk6U1geydctPNJEzKQG5Qhbo0KUPV5OWNTwWGYyqoA+wZnkuL20uo77VxpikCIpy4nmlXzlkgAsXu6lu6qap3X/WWddiY+7kJLp7XHRanUTo1dw6NZm/7uj75XC5fbg9PiakGTlb14VSIaNkVkagfk+vw027xUF0pGbAmPIzTUzNjuFohf9GbtEQWtN7o1hdNl4/9w7V3XVk9SuoNifZX/ultdfMc0d/GTjzzzGNo8PRFQj4AFa3jZNtZcxMLAzJe7gZwpIGTqmo4weeXCjC1BjnL8A4fwGAv6Z+P15LFzFfuAvH+b58E0PBNDSpaUR/roQ2jwef0+lvriKTEbvyi8TctQpkshFZxbS/mHgDMfH+TNryE00DHu+xOoLKMwB0ddpZcX8B5SebUKuV5BckoVIPj6nHURf0U+IM/PDrM/B4fSgV8qCz98vUSnkg4F9W22zlp98oxtzlICZSw/nGgQ3PVUoF/1aSx85jDWjDlMy/VFLVv4LnIgBp8QbS48OpbbEik8GiwlTS4v1z98tn6Qe85ki1ofw1zrSfBaDD0YnD4+Qbk78WeHx3w4eBgA9Q3nGOaM3AqRydcmQXrYu4ZQ69Z8uwHTuKTKEgaslSIufdivXIYewV/s9PER6BoXBGULe28IJCunZ+EHgdXV4+kbfMQRUXh7X0EEqjEdPty3B3dtL4wvNIbv+a9dZX/ojSaMQwacqQb5RyI2SNj+XI/r5WiGEaJRMLUzh3pjXoRm5cYgSxCeHEDsP7bqMu6F92eUlkekI486Yksee4PygnxehZOjOdg2UtOPr9kBOidVy81GpNqZAzLtXIuJTIQFMWjVpB4fhYHn+5FNulpI+9Jy7ylSXjAwEf/FcNd83L4oHlOejClJgiBp75jwblHecG3ba6bCjlStzege3ockzZVHadp6XXX90025hFXvSEGz/YEJKrVCR945t4LBZkKhUKnX8qK+U736Pn1EkcdbV0f7if+h8/gSo2jsR//99o0jOIWXkPcp2O3vIyNOnpRN/xBQB6z5zGsm8PeL30njlNeNHMQMC/rOfkSQyjcP0++IP83V+dRsWpZrxeifH58RgiNCy6M5d92yuxdTvIHBdD4ezhO90lCq5d0tTeg83uZkxSJHK5jANnmtmwrQKHy0titI5wnSrQICU/y8SDd03C65PY9M9quqxOlhanc+ycmY37qoNed0FBMjuvaKE2f0oSq28f2cHqkzxz+OfUW/s+l9TwZExhRk60nUEpV1KUUMChpqN4JP8f3iR9Ao9O/zYSEmc7KlHJVWRHZY3YevqXST4flr27L9XOSSdq0ZJA60SA2id/gLO2JrAdlpZO+mM/HPS1nI0N1D7+30H7IufOx7J3d9C+2Pu+TNSChdftPYwkPp8P+TC4AhIF165B/9r5AMV5CRRkx9Jlc3LhooWXNvfdgD19oYMjZ1s5WNbCyUtZfKeqOwa9kZsaZ0CvUQZ64sqA6cPgDv+N9qUJd/Py6T/Tam8jThvDuKgx7KjbC/jbKe6/WMoDeV+mztqAQa1nVuKMQAG2/JicUA79pmrftJGOzZsAsB09grO+jqR//4/A485+BdjAH9gddbV0bN6E12Yjcs5cIor9DT3crS0DXt/ndmFaXkLn1i1IHg+GqdOInDP3Br6j4W04BPxPIoL+VVhsTurNNrISI+i0DUwSq2ywBAI+EEjcitCr6b60EigxWsfMvATGJEWy5VAtvQ4Pc6ckkTNE6mqHUmp4Mo/N/B42dw8GlZ6/Vrw54Biv5OXzY5eFYHRDR/eHwUsnbUeP4HM48Nrt+Oy96PMn0nOib129bkIODc/9BF+vfyrSfq4CuVaHYcpUtONzkOt0gccADFOmYpg8lajFS5HcbiSPh9ZXN+A2t2IomIbxtkUj/kbuaCOC/iAOnG7m5X+U4/VJhKkU3LfIXxP/8pJKpUJOZlIEuz4KnrZBBk88MIPD5a2olHKmT4gjTKUgJc7AmuW5/jrdcvEFukwmkxGu9q+ayIuewP6LpYHHVHIl46LGhmpoQ4YiIgJPR9/JhVynw/z2m1h2fgCSRFhGJobC6ThqqtGOGYsuL5/eM6eDXsN29AgyhQLLvj1ox41HcjqRPB6UUSZa/vQHml2/IWLOXGLvuY+6H3wfV7N/BYv9XAVIElGLljCcDZcpmZtFBP0r+CSJv+2sDJRIdrq97DjawMP3TmX7Ef+l9KLCFLKSIth6qI6Lbf6qhQq5jDmTEtl6sI49JxrRhilRKeQU5yew+3gjb+25gMPlZc7kRL60cJwI/leYHJvPPeO+wP6Lh9AqNSzLXEhk2PBbGXG9xd61ksZf/BzJ6fSXXJh/Gx3vbQo87qypxjC1IDDlc+V0DwByGY0vPB8o0qYwhJP4rW/T8PSPAodYdu1EEREZCPiXWY8eGbZBv7O9hx3vnsXcbCUuMZzbSnKIjNJy/FA9VeWthEdqmDE3E1OMnot1XZw80oBMBpOmp5J4nTJqS/dWc+poIyqVnMJbMsgNQZP0K93QoH/ixAmee+45NmzYQG1tLY8++igymYzs7Gwef/zxIfnX1+v1BVbfXGbpcdFmsdPQasPt8XK+MYLsFCOPfqmAvScu0t3jojgvgbpWK1tL6wCwO7387r0yIgxqNmytCGT47jrWSHp8OHMnh/6HP5T4JB8tva209JrRKMNos3cybmCi8qijy8kl66f/g/18FWEpqTguVA04xm1upe2tN7Ds/yfKiHAMhdOxHTsKPh+aMWP9tcD7rdfw2qxYD3w48HXa2/wN1/tl7Q5I6BpGdv2jAvOlJdmtTVZ2/eMsYybEcXC3v7haW4uN1iYrn1uVz7t/PxFItKqtamfVA9MxDlJJ9+O4XV5qqtpQKOSBevpHP/RnO7ucsGfrOeKTIgLdtULlhgX9l156iU2bNqHV+tdRP/300zz00EMUFRXx2GOPsWPHDhYtWnSj/vlPTaVUMH1CHKXlfd1xJmVF89LmssD35rVdVSRE64gzamk027D2umnp7B1Q4kGS4FhF64BOrxcudougf4UDTYfZ3eCfv3a73Pzl7BuMNWYQp4sN8chCT6HXY5g0GQB5WB5yrRafva+JvEyppuMf/h7DXksXrpYW0h9/EplchjoxifZ33xnwmroJE/yrdvp12jLkT0KTlk7ba39D8nhQxcUTfecXbuybu4Fa+/W78G9bUVxRvbbH6uT00YuBgA/g9UpUV7YxtSgNn08a9Krc7fLSUNOBVqcmISUSe6+LN/90LFCPJybeMGj9neZGy8gN+mlpaaxfv56HH34YgDNnzjBjhr+k8Ny5c9m/f/+QDPoAX1+WQ3KMnppmKxPSo5DLZUgngy97z1R38MfyFrp7/VcFp6s7uG1acPakTOZfqbPneFNQLZ3xlzrtCH1qLHVB2xISNd31IuhfQaHXk/K9R+l47118vb1EzpmH9VIT88sklwtXcxOO81X0lpehSkpCnZiEq8mfLxIx6xbCC2eABG3vvIXP4cA4f4G/AicQMb0Id2cHYSmpwzpBKzHVyMW6rsB2UpoRo0lLY23fPrlCRnTswKRIn8fH335XSmdbL8npRm4ryUFv8Feu7O6y8/arH9F7aYHH2Jw4YhMMQQXY2lpsJKUO/J7HJ4W+ENsNC/pLliyhoV9Z1/7Zgnq9Hqv1k9fgR0XpUCpDk9r89c/3/cDO1XXy5+3ByUQR4WGBgH+ZxwefnzeGrQdq0GtVrF6Ww5zCNFAqeXVLOb0OD0uK0ymZN1asiLjCFFsOHzYdDmzLZXKmZ+YRaxDz+gPE5pM6LT+w2eCwYjvS99khl+MuO0nnHv8SWGd9HRH5eYx/6Jso9Xp0qf56/LHLbiNr2W2DvH44MPyvRFeunsbm109SX9NJamYUy++ejEIpp8Pcw8V6Cyq1gkUluUydkUZTfTdVl3rfZufGc+5MC10d/qupxtoujuyr4e7V/nIfR/9ZGwj4AFXlrUQMUl4lPSuaCKOWw/+sRqlSMG/xOHLyEwccd7PdtBu5/efve3p6iLiG2tydnb2feMzNEKVVsnL+GDYfqMHtkZg/JYnJWSbe3n0+6LhwrZI7itO5o7gvW89stjIhOYIfrSkK7GtrC+7PKUCuPo/F6beyv9F/I7ckawkyexhm+81L0BuuVMVzCa84j/XwIRR6PTF3r6LtreAlsN2nz2DXRyHXaOm5iUmPobb4C3mB/3d5POCBO780le4uOxqtCnWYko7OHhZ9Ppdp5nSQ+dsp/ml98D2P+uqOQLJo1yBxyRijQx2mwOX0JxPqDGpikwykZEUxsbBvBuBmJZwOieSs3NxcDh06RFFREXv37mXmzJk365++LpbOTGfxjFQkqa+Ew5IZqWwvrUcC0uIMLCocOn0whxuZTMadY5Zy55iloR7KsCNXqUn8t/9F/Fe/hkyhRCaX0/3hfuyWvmkMZZQJmfrqjTVGmwjjwJpNpn7TPMZoHV396m/FJUVQuq8aa5cDo0mLTNZ3bzwySsvYnDgSkiM4e7IZhUJOzuREwjSqG/4+Po0bWoahoaGB73znO7z22mtUV1fz/e9/H7fbTVZWFj/60Y9QKD5+6uZmlmEYzNGKVs7UdJIWb+CWiYmDtjBstziw2d2kxRsGnbLp7nXxwZEGLDYnM3PjRWLWx9hZv49/Nh5Cp9SwLHPRqO+Q9Vk46+tp/MX/w9PejtxgIHHNWvT5kz75iQIA7WYbe7edo721h9TMKCydDtr7lWSfNjudXpsLnV5N/rRkdHr1x7zazfdxZ/qi9s5VbD1Ux2u7+pbHzZ6YwAOfy/3Y5+z6qJF/HKhFQuL2GWksKEjhsZdLA2v5ZcBDqyYzcZjU3b6ZjrWe5PenXw1sK+VKflj8CMaw0N/4Gq4knw93ayvKaBNy1dAKSsNJe6uN114OvlmekhFFyRcnh2hEn+zjgv7wvTV/g+0+Hpxte+B0Cw6X5ypHQ1WjhQ3bKmjvdtDR7eQvH1Sy42hDIOCDf7n0vpMD63ULUN5+Rds+n4dzneevcrRwLWRyOeqEBBHwP6MwjZIrL+I1uqE5dXMtRNC/Cs0VDRFUKjmKj1m+dq6+a8C+5o6BN3wMGpEEPZhkw8BVDYPtEwbnMrfSuX0r1sOlSF7vJz9BuGaGCA2TpqcEtjVaJQXFoWt6/lmJCHQVd96SyYtvnw6UY5iRE8ev3zmNSinn9qI0MhIisDs9fHi6GWuvi5hBlmxNHhuDy+Nl/yl/a7sIvZolRcP3l+VGmp1cxAVLDcdaT6KSK1mauVAE/WtkP19Fw3M/CdTF10+aTPKD60I8qpFl1oKxjM9PoNviIDnNiDps+IZOMaf/MdosdirqupDLZfyuX0ZumErBj9cU8cJbJ6lr8d/cUSnlzJ6YwMEzLUgSLJ6eyhfmZgH+DNwum5O8DBNhw6SlWqj0uu0o5UrUiuF7+XyzNf3mRayHS4P2pf/gSXwuF/az5YSlpaPPnxii0Y0MPp+PCxVtWC0OMrKjiYoe2l3uhsSSzeEoJlJLzEQtr+2q6l+6BKfby/Yj9YGAD+D2+PD5JH6xbi5cUU0zK2l0NTn/LHSqkd3+8EYY7LzNeuwoHZs2Brajln6O2LtW3sxhjSjbN5ZRfa4N8BdRW37PJJLTh2dxKDGnfw2iB2lpaDQMXPOsUMiRy2SigqZwUxkXLESm7Dt/0+XmYS09GHRM1wfb8bkHtqAUPllXR28g4AP4fBInDzd8zDOGNhH0r8EtExMZ1694UlFuPIump5DT7y+9LkzJwmkpgz1dEG4o3bjxpD32BNGfX0H819aQ9K2HGFDlD7jKTuFTGM6fpJjT/xfUtVhRqxQkXCq56vH6OF7ZhtXupiA7hshBzv4FIRQse/fQ8sofAttRty8j9u5VIRzR8LblzVPUVPqb2cjlsiE/vSOSswRhFLJXVdJ7tpywtDQMk6aEejjDmtfr40KFme4uB5njYjDFDN8buSLoC0OG3ePgdFs5WqWG3OjxyGVi9lEQPg2xekcY8jodXTx75BdYXP7GF9nGLB6culYEfkG4zsQ3ShgS9jYeCAR8gMquC1R0DmwNKAjCZyOCvjAkuLyuAfucg+wTBOGzEUFfGBKKE6ejkvfNNkZrTOSaRGllQbjexI1cYci4aGvmYPMRdEots5OKCFeHtoG0IAxXYvWOIAjCKCLq6QuCIAiACPqCIAijigj6giAIo4gI+oIgCKOIyMgVhBGq91wFveVlaNLS0U+ZiuzKRq/CqCSCviCMQF17dtG64U+B7ahFS4i9594QjkgYKsT0jiCMQJ3btwZtd+3agc8tMpwFEfQFYUSSXVmoTi4HxPSOIIK+IIxIpmXLod8cftTiJchVotm8IDJyBWHEctTW0Hu2HE1aOrqc3FAPR7iJRBkGQRCEUUSUYRAEQRAAEfQFQRBGFRH0BUEQRhER9AVBEEYREfQFQRBGERH0BUEQHKsE0gAABX5JREFURhER9AVBEEYREfQFQRBGkSGdnCUIgiBcX+JMXxAEYRQRQV8QBGEUEUFfEARhFBFBXxAEYRQRQV8QBGEUEUFfEARhFBFBXxAEYRRRhnoAQ9kzzzzDmTNnMJvNOBwOUlNTqayspLi4mOeffz7UwxsRGhoauOOOO8jLywvsKyoq4pvf/GZge926dfzkJz9BrVaHYojDwm9/+1s+/PBD5HI5MpmMdevWkZ+fP+ixf//731mxYgUq0T5xUP/KZzksScInevPNN6Vnn31WkiRJOnjwoPTQQw+FeEQjR319vbRy5cpQD2NYq6yslO655x7J5/NJkiRJZWVlUklJyVWPv/XWWyWHw3Gzhjes/Kuf5XAkpnc+hdraWtasWcOKFStYv349APfffz/nz58H4K9//Svr16+noaGBkpIS7r//fl566aVQDnlYOXToECtXruS+++5j48aNLFiwAKfTGephDVkmk4mLFy/yxhtv0NLSQk5ODm+88QalpaWsXr2a1atXs2rVKqqrq3n99dcxm82sW7cu1MMekq72WV7t+33PPffw7W9/mxUrVvD444+HePTXRkzvfApOp5MXX3wRr9fL/Pnz+da3vnXVY81mM2+++aaYmvgYVVVV3H///YHtlStX4nQ6ef311wF44YUXQjW0YcFkMvGrX/2KV199lV/+8pdoNBrWrVtHW1sbzz77LPHx8fz6179m69atfOMb3+BXv/qVmJ68iqt9lldTU1PD73//e7RaLQsXLsRsNhMbG3sTR/yvE0H/U8jOzg4EcaVy4Eco9StnlJKSIgL+Jxg7diwbNmwIbB86dIjMzMwQjmh4qa2txWAw8PTTTwNw6tQp1q5dy8MPP8yPf/xjdDodLS0tFBQUhHikQ9/VPsuYmJjAMf2/32lpaRgMBgBiY2OHxRWpmN75FGQy2YB9arUas9kMQFlZWWC/XC4+4k9DfG7XrqKigh/84AeBgJOZmUl4eDhPPfUUTz31FM888wxxcXGBYCWTyfD5fKEc8pB1tc/SaDQO+v0eLBYMdeJM/zpZvXo1TzzxBImJicTFxYV6OMIosnjxYs6fP8/KlSvR6XRIksTDDz/M4cOHWbVqFREREcTExNDa2gpAYWEha9eu5ZVXXhmWQetGutpnqVKpRsz3W5RWFgRBGEXENbQgCMIoIoK+IAjCKCKCviAIwigigr4gCMIoIoK+IAjCKCKCviBcg0cffZS33nor1MMQhM9MBH1BEIRRRKzTF4RBSJLEM888w+7du4mLi8Pr9XL33XdTW1vLgQMHsFgsxMXF8fzzz7Nr1y4OHjzIz372MwDWr19PWFgYa9euDfG7EISBxJm+IAxi27ZtlJWVsXnzZn7+859TV1eH1+vlwoUL/O1vf2Pbtm0kJiayadMmli1bxoEDB7DZbABs3ryZO++8M8TvQBAGJ8owCMIgSktLWbx4MSqVCpPJxNy5c1EoFDzyyCO8/vrrVFdXc/z4cdLS0tDr9cybN4/333+f1NRUUlNTiY+PD/VbEIRBiTN9QRiETCYLqqaoVCrp6urigQcewOfzsWTJEhYuXBg45q677mLz5s28++67rFixIlTDFoRPJIK+IAyiuLiYLVu24HK5sFgs7Nu3D5lMxowZM7j33nvJyMhg9+7deL1ewF/ErLm5mUOHDrFw4cIQj14Qrk5M7wjCIBYuXMipU6dYvnw5MTExjBkzBofDwdmzZykpKQEgPz+fhoaGwHMWLVpEV1eX6J8gDGli9Y4gfEaSJOF2u/na177Gf/7nfwY1eReEoUZM7wjCZ2Q2m5k9ezaTJ08WAV8Y8sSZviAIwigizvQFQRBGERH0BUEQRhER9AVBEEYREfQFQRBGERH0BUEQRpH/D1uMlPHoGEpyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(\"day\", \"total_bill\", data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 类别内数据分布\n",
    "## 箱型图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2945fcc0>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(\"day\", \"total_bill\", data=data, hue=\"time\", palette=[\"g\", \"r\"], saturation=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 绘制提琴图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a29596b00>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(\"day\", \"total_bill\", data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 类别内的估计统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a295f2550>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(\"day\", \"total_bill\", data=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a29866d68>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pointplot(\"day\", \"total_bill\", data=data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
